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Related Concept Videos

Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
What is Population Genetics?01:25

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.

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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

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Published on: July 4, 2007

Computer simulations: tools for population and evolutionary genetics.

Sean Hoban1, Giorgio Bertorelle, Oscar E Gaggiotti

  • 1Laboratoire d'Ecologie Alpine, UMR CNRS 5553, Université Joseph Fourier, BP 53, 38041 Grenoble, France.

Nature Reviews. Genetics
|January 11, 2012
PubMed
Summary
This summary is machine-generated.

Computer simulations are now accessible to more researchers, transforming fields like genetic epidemiology and evolutionary genetics. This review guides their use for understanding complex genetic processes and data analysis.

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Area of Science:

  • Computational Biology
  • Evolutionary Genetics
  • Genetic Epidemiology

Background:

  • Computer simulations are powerful tools for analyzing complex evolutionary and genetic processes that defy analytical prediction.
  • Historically, simulation use was limited to researchers with programming expertise, but software advancements have increased accessibility.
  • In silico genetic data, combined with population genomics data, are revolutionizing multiple scientific disciplines.

Purpose of the Study:

  • To review the current state-of-the-art in simulation software for biological research.
  • To identify diverse applications of computer simulations across scientific fields.
  • To evaluate the capabilities of various simulation tools and provide guidance for their effective use.

Main Methods:

  • Comprehensive review of existing simulation software packages.
  • Analysis of the capabilities and features of different simulators.
  • Identification of current and potential applications of simulation in relevant research areas.

Main Results:

  • Dozens of sophisticated, customizable simulation software packages are now available, broadening accessibility.
  • Simulations are increasingly used in genetic epidemiology, anthropology, evolutionary and population genetics, and conservation.
  • The integration of in silico genetic data with population genomics data is driving significant advancements.

Conclusions:

  • Computer simulations are essential, accessible tools for modern biological research.
  • The review provides a guide to aid researchers in selecting and utilizing appropriate simulation software.
  • Future directions in simulation software development and application are summarized.